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Based on the studies, the strategy to design a thermal imaging hardware and software complex to monitor inflammatory processes in animals has been developed. Analysis of temperature indices in various healthy cow body areas has been carried out. The reasons for animal body temperature change during physiological processes caused by developing inflammation foci in the cow mammary gland and weight-bearing joints at subclinical disease period have been considered. Parameters of thermal imaging and associated equipment required to detect temperature abnormalities caused by inflammatory processes have been analyzed. The methods of thermal image segmentation, as well as their traditional histogram analysis and new methods of phase portrait analysis, have been reviewed. The key features of thermal image formation and processing aimed to monitor inflammatory processes in animals are discussed.

The paper present a neuroevolutionary method of monochrome and color images enhancement. The proposed method is based on local-adaptive approach to image processing. Neural network is tuned to perform enhancement of particular image using genetic algorithm with use of the generalized image evaluation criterion that relies on the contrast degree of the processed image.

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